Development and validation of a RNA binding protein gene pair-associated prognostic signature for prediction of overall
- PDF / 1,906,005 Bytes
- 15 Pages / 595.276 x 790.866 pts Page_size
- 27 Downloads / 211 Views
BioMedical Engineering OnLine Open Access
RESEARCH
Development and validation of a RNA binding protein gene pair‑associated prognostic signature for prediction of overall survival in hepatocellular carcinoma Chunmiao Kang1†, Xuanhui Jia1† and Hongsheng Liu2* *Correspondence: [email protected] † Chunmiao Kang and Xuanhui Jia contributed equally to this work and should be considered co-first authors 2 Department of Radiology, Xi’an Central Hospital Affiliated to Xi’an Jiaotong University, No. 161, Xiwu Road, Xincheng District, Xi’an 710003, Shaanxi, PR China Full list of author information is available at the end of the article
Abstract Background: Increasing evidence has demonstrated the correlation between hepatocellular carcinoma (HCC) prognosis and RNA binding proteins (RBPs) dysregulation. Thus, we aimed to develop and validate a reliable prognostic signature that can estimate the prognosis for HCC. Methods: Gene expression profiling and clinical information of 374 HCC patients were derived from the TCGA data portal. The survival-related RBP pairs were determined using univariate cox-regression analysis and the signature was built based on LASSO analysis. All patients were divided patients into high-and low-risk groups according to the optimal cut off of the signature score determined by time-dependent receiver operating characteristic (ROC) curve analysis. The predictive value of the signature was further validated in an independent cohort. Results: A 37-RBP pairs signature consisting of 61 unique genes was constructed which was significantly associated with the survival. The RBP-related signature accurately predicted the prognosis of HCC patients, and patients in high-risk groups showed poor survival in two cohorts. The novel signature was an independent prognostic factor of HCC in two cohorts (all P
Data Loading...
